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Federal Highway Administration Research and Technology
Coordinating, Developing, and Delivering Highway Transportation Innovations
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Publication Number: FHWARD98156 Date: FEBRUARY 1999 
Introduction 
A second method used to demonstrate the Level 1 PRS prototype specification involved developing general pay factor charts for typical designs within a chosen SHA. As a followup to the original shadow field trial, the research team developed Level 1 pay factor charts representative of three typical pavement designs used in Iowa. The objectives of this exercise were twofold:
This chapter explains the details of selecting the different pavement designs, the development of the respective pay factor charts, an analysis of the observed trends within and between the developed charts, and the conclusions and recommendations resulting from this exercise.
The first step was the selection of three typical PCC pavement designs used in Iowa. Each pavement design was selected to be specific to an assumed traffic level representing medium, heavy, or very heavy traffic. All three pavement designs were assumed to have a 40year design life. The chosen cumulative ESAL values (over the 40year design lives) for each of the chosen traffic classifications consisted of the following:
For the development of these pay factor charts, pavement performance was defined in terms of all of the four available distress indicators (i.e., transverse slab cracking, transverse joint faulting, transverse joint spalling, and pavement smoothness over time).
For the three chosen typical designs, Level 1 pay factor charts were developed for each of the following four AQC’s:
The representative constant values required to simulate the corresponding pay factor charts (for the three chosen designs) were determined based on information provided by Iowa SHA personnel. Values for the climaticrelated variables and unit costs were assumed to be the same as those used at the original PRS field trial conducted in Wapello County, Iowa, in 1996 (see chapter 2 of this volume). More information on the selection of constant variables is presented in chapter 5 of volume I, in the section titled Identification of Constant Variable Values. The specific values chosen to represent each of the three typical designs are presented in table 71. (Note: The constant inputs presented in table 71 are those required by the old distress prediction models used in the prototype PaveSpec software.^{(13)} These variables differ slightly from those constant values required by the new distress indicator models included in the revised PaveSpec 2.0 software [as shown in figure 1 of volume I].)
Variable 
Design 1 (Medium Traffic) 
Design 2 (Heavy Traffic) 
Design 3 (Very Heavy Traffic) 


Project Information  
Pavement Type 
Doweled, JPCP 

Road Location 
Rural Setting 

Highway Type 
Undivided 
Divided 
Divided 

Design Life 
40 years 

No. of Lanes in One Direction 
1 
2 
2 

Lane Width 
3.7 m 

Joint Spacing 
6.1 m 

Traffic Information  
Total Design Traffic 
2.5 MESAL’s 
7.5 MESAL’s 
30.0 MESAL’s 

Initial Year Traffic 
62,500 ESAL’s 
187,500 ESAL’s 
750,000 ESAL’s 

Traffic Growth Type 
Simple Linear Trend 

Materials and Climatic Information  
Annual Temperature Range 
22 ÂșC 

Freezing Index 
750 degreedays 

Average Annual Precipitation 
81.3 cm 

Projected Annual FreezeThaw Cycles (at 7.6 cm below the pavement surface) 
12 

Salt Present 
Yes 

Joint Sealant Type 
Liquid Asphalt 

Slab Support Information  
Base Type 
Granular 

Modulus of Subgrade Reaction 
40.7 MPa/m 

Subgrade Soil Type 
Finegrained (AASHTO A4A7) 

Presence of Longitudinal Subdrains 
Yes 

Load Transfer Information  
Dowel Bar Diameter 
3.2 cm 
3.8 cm 
3.8 cm 

Presence of Tied PCC Shoulder 
Yes 

Cost Information  
Construction Bid, Traffic Lanes (based on $86.32/m^{3}) 
$17.89/m^{2} 
$20.08/m^{2} 
$23.32/m^{2} 

Cost of Asphalt Overlay 
$10.76/m^{2} 

Cost of Patching a Joint 
$95.68/m^{2} 

Cost of Replacing a Slab 
$83.72/m^{2} 

Assumed Asphalt Overlay Life 
20 years 
Four different AQC’s were chosen to demonstrate the Level 1 PRS approach for each of the three typical designs. These included 28day flexural strength (thirdpoint loading), slab thickness, plastic entrained air content (using a pressure meter), and initial smoothness (measured using a 5.1mm blanking band). The AQC target means and standard deviations for each of the three designs were estimated by interpreting the current Iowa construction specifications. These values were determined using the same procedures utilized in determining the target values at the original Iowa field trial in 1996 (see the section titled Definition of the Required AsDesigned AQC Target Values in chapter 2 of this volume). The chosen AQC asdesigned target means and standard deviations are presented in table 72 (the actual specification design thickness means are shown as a comparative reference).
Table 72. Chosen AQC asdesigned target values for three typical pavement designs in Iowa.
AQC 
Design 1 (Medium Traffic) 
Design 2 (Heavy Traffic) 
Design 3 (Very Heavy Traffic) 


28day Flexural Strength (thirdpoint loading)  
PRS Target Mean 
4.48 MPa 

PRS Target Std Dev 
0.45 MPa 

Slab Thickness  
Specification Design Mean 
203 mm 
229 mm 
267 mm 

PRS Target Mean 
207 mm 
233 mm 
271 mm 

PRS Target Std Dev 
6 mm 

Entrained Air Content  
PRS Target Mean 
7.0% 

PRS Target Std Dev 
0.5% 

Initial Smoothness (5.1mm blanking band)  
PRS Target Mean 
79 m/km 

PRS Target Std Dev 
16 mm/km 
A number of simulationrelated parameters are required to simulate LCC’s representing the asdesigned and asconstructed pavement lots. The individual Level 1 AQC pay factor charts were simulated using the following simulation parameters:
These simulation parameters are used in conjunction with the defined constant variable values and selected AQC target values to generate the preconstruction output.
The final step in the specification development process involves the development of the preconstruction output. For the Level 1 specification, this involves constructing individual pay factor charts (and corresponding pay factor equations) for the four AQC’s. Individual AQC pay factors may be computed using these equations by knowing the asconstructed AQC lot means and standard deviations. (Note: Each pay factor chart is specific to the chosen constant values, target means, and standard deviations.)
StepbyStep Procedure Used to Develop Individual Level 1 AQC Pay Factor Curves
The following stepbystep procedure was used to develop Level 1 pay factor charts and corresponding pay factor equations for the three typical Iowa designs. (Note: Each of these steps is accomplished using the PaveSpec PRS demonstration software.)
Table 73. Asconstructed AQC simulation mean ranges for the three typical
AQC 
Design 1 (Medium Traffic) 
Design 2 (Heavy Traffic) 
Design 3 (Very Heavy Traffic) 

28day Flexural Strength (thirdpoint loading), MPa 
3.78 – 5.18 

Slab Thickness, mm 
187 – 227 
213 – 253 
251 – 291 
Entrained Air Content, % 
0.0 – 7.0 

Initial Smoothness (5.1mm blanking band), mm/km 
0 – 240 
Table 74. Asconstructed AQC standard deviation levels for simulation
AQC 
Design 1 (Medium Traffic) 
Design 2 (Heavy Traffic) 
Design 3 (Very Heavy Traffic) 

28day flexural strength (thirdpoint loading), MPa 
0.00, 0.45, 0.90 

Slab thickness, mm 
0, 6, 13 

Entrained air content, % 
0.0, 0.5, 1.5 

Initial smoothness (5.1mm blanking band), mm/km 
0, 16, 79 
 Design 1 (Medium Traffic): LCC_{DES(1)} = $668,709/km.
 Design 2 (Heavy Traffic): LCC_{DES(2)} = $706,135/km.
 Design 3 (Very Heavy Traffic): LCC_{DES(3)} = $722,795/km.
To better demonstrate the PRS method, the estimated typical distresses over time associated with each of the three Iowa designs (reflecting the chosen constant inputs and the AQC target means only) are presented in figure 14. These distresses reflect the predicted first overlay application at year 33 for Designs 1 and 2, and year 30 for design 3. The M & R plan defined for the original Iowa field trial was also used here.
Figure 14. Estimated typical asdesigned distresses over time associated with each of the three typical designs (reflecting the chosen constant inputs and the AQC target means only). 
AsConstructed Means 
Simulated pay factors at different asconstructed standard deviations, % 


28day Flexural Strength (thirdpoint loading), MPa 
SD = 0.00 MPa 
SD = 0.45 MPa 
SD = 0.90 MPa 
3.78 
48.6 
47.3 
43.4 
4.48 
101.3 
100.0 
93.4 
5.18 
128.8 
127.9 
123.8 
Slab Thickness, mm 
SD = 0 mm 
SD = 6 mm 
SD = 13 mm 
187 
49.8 
48.8 
46.6 
207 
99.2 
100.0 
98.1 
227 
126.9 
127.2 
126.6 
Entrained Air Content, % 
SD = 0.0% 
SD = 0.5% 
SD = 1.5% 
2.0 
67.4 
66.8 
66.0 
7.0 
101.8 
100.0 
97.5 
Initial Smoothness (0.0mm blanking band), mm/km 
SD = 0 mm/km 
SD = 16 mm/km 
SD = 79 mm/km 
0 
112.5 
112.5 
110.8 
79 
100.6 
100.0 
99.2 
240 
58.6 
58.2 
57.3 
AsConstructed Means 
Simulated pay factors at different asconstructed standard deviations, % 


28day Flexural Strength (thirdpoint loading), MPa 
SD = 0.00 MPa 
SD = 0.45 MPa 
SD = 0.90 MPa 
3.78 
70.9 
67.7 
61.6 
4.48 
100.5 
100.0 
94.9 
5.18 
115.9 
116.1 
113.5 
Slab Thickness, mm 
SD = 0 mm 
SD = 6 mm 
SD = 13 mm 
213 
74.7 
73.4 
71.5 
233 
100.7 
100.0 
99.5 
253 
114.4 
114.3 
114.0 
Entrained Air Content, % 
SD = 0.0% 
SD = 0.5% 
SD = 1.5% 
2.0 
77.1 
76.9 
76.7 
7.0 
101.0 
100.0 
98.5 
Initial Smoothness (0.0mm blanking band), mm/km 
SD = 0 mm/km 
SD = 16 mm/km 
SD = 79 mm/km 
0 
107.1 
107.1 
106.0 
79 
100.5 
100.0 
99.9 
240 
79.1 
78.8 
78.4 
AsConstructed Means 
Simulated pay factors at different asconstructed standard deviations, % 


28day Flexural Strength (thirdpoint loading), MPa 
SD = 0.00 MPa 
SD = 0.45 MPa 
SD = 0.90 MPa 
3.78 
74.1 
72.3 
67.7 
4.48 
101.7 
100.0 
93.6 
5.18 
119.0 
118.1 
114.0 
Slab Thickness, mm 
SD = 0 mm 
SD = 6 mm 
SD = 13 mm 
251 
79.1 
78.7 
76.7 
271 
100.7 
100.0 
99.2 
291 
116.4 
116.0 
115.8 
Entrained Air Content, % 
SD = 0.0% 
SD = 0.5% 
SD = 1.5% 
2.0 
85.4 
84.6 
83.8 
7.0 
100.6 
100.0 
99.1 
Initial Smoothness (0.0mm blanking band), mm/km 
SD = 0 mm/km 
SD = 16 mm/km 
SD = 79 mm/km 
0 
106.6 
105.2 
103.4 
79 
100.4 
100.0 
99.3 
240 
84.9 
84.6 
84.2 
Figure 15. Design 1 (medium traffic)—simulated Level 1 individual AQC pay factor charts for the case of four sublots per lot and four samples per sublot (lot sample size N=16). 
Figure 16. Design 2 (heavy traffic)—simulated Level 1 individual AQC pay factor charts for the case of four sublots per lot and four samples per sublot (lot sample size N=16). 
Figure 17. Design 3 (very heavy traffic)—simulated Level 1 individual AQC pay factor charts for the case of four sublots per lot and four samples per sublot (lot sample size N=16). 
AQC 
AsConstructed Standard Deviation 
Pay Factor Regression Equation, x = mean value 

28day Flexural Strength (thirdpoint loading) 
0.00 MPa 
PF_{S(x, 0.00)} = –25.7189x^{2} + 287.7179x – 671.4876 
0.45 MPa 
PF_{S(x, 0.45)} = –25.3191x^{2} + 284.4695x – 666.2597  
0.90 MPa 
PF_{S(x, 0.90)} = –19.9880x^{2} + 236.5143x – 565.0175  
Slab Thickness 
0 mm 
PF_{T(x, 0)} = –2.7195E02x^{2} + 13.1846x – 1464.7132 
6 mm 
PF_{T(x, 6)} = –2.8791E02x^{2} + 13.8807x – 1540.1355  
13 mm 
PF_{T(x, 13)} = –2.8768E02x^{2} + 13.9090x – 1548.3911  
Plastic Entrained AirContent (for 0 to 7% only) 
0.0% 
PF_{A(x, 0.0)} = 6.8683x + 53.6719 
0.5% 
PF_{A(x, 0.5)} = 6.64x + 53.52  
1.5% 
PF_{A(x, 1.5)} = 6.315x + 53.335  
Initial Smoothness 
0 mm/km 
PF_{SM(x, 0)} = –4.6066E04x^{2} – 0.1139x + 112.45 
16 mm/km 
PF_{SM(x, 16)} = –4.2248E04x^{2} – 0.1246x + 112.48  
79 mm/km 
PF_{SM(x, 79)} = –4.7001E04x^{2} – 0.1100x + 110.8 
AQC 
AsConstructed Standard Deviation 
Pay Factor Regression Equation, x = mean value 

28day Flexural Strength (thirdpoint loading) 
0.00 MPa 
PF_{S(x, 0.00)} = –14.5726x^{2} + 162.7450x – 336.0902 
0.45 MPa 
PF_{S(x, 0.45)} = –16.5210x^{2} + 182.6422x – 386.6551  
0.90 MPa 
PF_{S(x, 0.90)} = –15.0809x^{2} + 172.2030x – 373.8903  
Slab Thickness 
0 mm 
PF_{T(x, 0)} = –1.5438E02x^{2} + 8.1861x – 968.5134 
6 mm 
PF_{T(x, 6)} = –1.6236E02x^{2} + 8.5896x – 1019.5902  
13 mm 
PF_{T(x, 13)} = –1.6794E02x^{2} + 8.8875x – 1059.5914  
Plastic Entrained AirContent (for 0 to 7% only) 
0.0% 
PF_{A(x, 0.0)} = 4.7850x + 67.5050 
0.5% 
PF_{A(x, 0.5)} = 4.6183x + 67.6719  
1.5% 
PF_{A(x, 1.5)} = 4.3700x + 67.9200  
Initial Smoothness 
0 mm/km 
PF_{SM(x, 0)} = –2.0616E04x^{2} – 0.0673x + 107.10 
16 mm/km 
PF_{SM(x, 16)} = –1.7625E04x^{2} – 0.0753x + 107.05  
79 mm/km 
PF_{SM(x, 79)} = –2.3768E04x^{2} – 0.0579x + 105.95 
Table 80. Design 3 (very heavy traffic)—Level 1 AQC bestfit regression equations for the case of four sublots per lot and four samples per sublot (lot sample size N=16).
AQC 
AsConstructed Standard Deviation 
Pay Factor Regression Equation, x = mean value 

28day Flexural Strength (thirdpoint loading) 
0.00 MPa 
PF_{S(x, 0.00)} = –10.5255x^{2} + 126.3893x – 253.3085 
0.45 MPa 
PF_{S(x, 0.45)} = –9.8374x^{2} + 120.8210x – 243.8380  
0.90 MPa 
PF_{S(x, 0.90)} = –5.4613x^{2} + 82.0068x – 164.2257  
Slab Thickness 
0 mm 
PF_{T(x, 0)} = –7.4090E03x^{2} + 4.9484x – 696.1730 
6 mm 
PF_{T(x, 6)} = –7.2153E03x^{2} + 4.8425x – 682.2020  
13 mm 
PF_{T(x, 13)} = –7.5020E03x^{2 }+ 5.0440x – 716.7401  
Plastic Entrained AirContent (for 0 to 7% only) 
0.0% 
PF_{A(x, 0.0)} = 3.0383x + 79.3319 
0.5% 
PF_{A(x, 0.5)} = 3.0733x + 78.4869  
1.5% 
PF_{A(x, 1.5)} = 3.0583x + 77.7019  
Initial Smoothness 
0 mm/km 
PF_{SM(x, 0)} = –7.3172E05x^{2} – 0.0727x + 106.60 
16 mm/km 
PF_{SM(x, 16)} = –1.2338E04x^{2} – 0.0561x + 105.20  
79 mm/km 
PF_{SM(x, 79)} = –1.7278E04x^{2} – 0.0384x + 103.40 